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Learner Reviews & Feedback for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization by DeepLearning.AI

4.9
stars
56,697 ratings
6,508 reviews

About the Course

This course will teach you the "magic" of getting deep learning to work well. Rather than the deep learning process being a black box, you will understand what drives performance, and be able to more systematically get good results. You will also learn TensorFlow. After 3 weeks, you will: - Understand industry best-practices for building deep learning applications. - Be able to effectively use the common neural network "tricks", including initialization, L2 and dropout regularization, Batch normalization, gradient checking, - Be able to implement and apply a variety of optimization algorithms, such as mini-batch gradient descent, Momentum, RMSprop and Adam, and check for their convergence. - Understand new best-practices for the deep learning era of how to set up train/dev/test sets and analyze bias/variance - Be able to implement a neural network in TensorFlow. This is the second course of the Deep Learning Specialization....

Top reviews

XG
Oct 30, 2017

Thank you Andrew!! I know start to use Tensorflow, however, this tool is not well for a research goal. Maybe, pytorch could be considered in the future!! And let us know how to use pytorch in Windows.

NA
Jan 13, 2020

After completion of this course I know which values to look at if my ML model is not performing up to the task. It is a detailed but not too complicated course to understand the parameters used by ML.

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226 - 250 of 6,433 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Satvik C

Sep 10, 2020

Andrew NG is such a fantastic teacher especially in this online mode. He provides crystal clear explanations and examples to understand why the methods work. As a learner I was only expecting to learn how to apply this to solve real problems and not to learn theoretical subtities, this is probably the best course in deep learning.

By Hari G S

May 13, 2020

Excellent course over all, but what I like the most is how the complex math behind all these techniques are carefully hid and instead, we're given an intuition about how these techniques work. Of course, for a deeper understanding much more mathematics is needed, but they make sure that everyone has an idea about why things work.

By Bernard O

Oct 23, 2018

The tips and great guidelines one gets from this course are gems in their own right. Practitioners in particular will get to appreciate all the usable advice to improve their neural networks and at the same time get to understand the principles behind the scenes on what truly drives those optimizations. Highly recommended course.

By Sinkovics K

Aug 15, 2018

The course material is detailed and comprehensive and presented in a very digestible way. I felt like the home works lack a few topics (e.g. learning rate decay implementation, which I would find to be a useful exercise), but they give you a good understanding of what is going on. All in all, I definitely recommend this course!

By jxtxzzw

Mar 16, 2020

After learning the basic knowledge of the first course, this course deepened my understanding of deep learning, and explained how to optimize the model of deep learning from the perspectives of hyperparameter tuning, regularization and normalization, and finally provided the basic knowledge of the framework based on TensorFlow.

By Kazi M R

Jun 6, 2018

From this course I have learnt several important hyper parameters, regularisation and optimization of deep neural network. Most importantly I got my first hand-on experience on Tensorflow framework by which creating deep net modes are quite easy if someone knows the elements of a deep net. I wish I will proceed for next course.

By Ian C

Oct 1, 2017

Learning about TensorFlow is brilliant. It's very hard to get a good understanding of what goes on in TensorFlow without fully understanding the neural network coding setup. This course beautifully combines the two. There were some minor frustrations with the final TensorFlow programming exercise, but overall this is excellent.

By Pawan S S

Jan 8, 2021

One of the rare courses teaching about structured hyperparameter tuning. All the subject matter are well taught and the flow of the module is very easy to follow and understand. Together with the programming assignments, I was able to quickly grab the essentials. I highly recommend this course for any deep learning enthusiast.

By Jeroen M

Jan 10, 2018

Great course, a few rough edges in the exercises and I also feel the exercise comments give away a bit too much (would be better if the student needed to figure out things by himself a little more). But these are minor details, I've learned a great deal in an amazingly short span of time, from one of the top minds in AI today!

By Jeff R

Oct 2, 2017

I appreciate the large amount of time that has gone into preparing this course. I note that there are a large number of corrections in the errata forum that have not been reviewed by staff. In particular there are some obvious errors in the programming assignments that could easily be corrected with a small investment in time.

By Pranshu A

Aug 22, 2020

Awesome, Amazing, Best, Fabulous course. Learnt a lot about Hyperparameter tuning and atlast got an intro about tensorflow framework which i wanted to start learning but earlier afraid from it's complexity which is explained so good in this course. Best course for Tensorflow Intro and Hyperparameter tuning in Neural Networks.

By Murat T

Dec 23, 2018

Topics cut in to sections are well defined and so clear. Programming assignments definitely gives you hands on experience. Also, math is demystified that you track with high school math. If you used framework like Keras and you want to know why and when you need to use that function,parameter etc., you would love this course.

By Gilles D

Sep 5, 2017

Eventually a clear and definitive explanation about Network initialization, regularization and optimization. Good insight share on hyper-parameters prioritization.

We learn the how and why and suddenly, it all becomes a little bit less mysterious. It is all clearly explained in a very accessible way.

Great value for my needs

By Xuefeng P

Aug 29, 2017

This course really gives you a fundamental and practical ideas about the hyper-parameters of DNN, and the way of tuning them. The part I liked most is the last programming assignment ---- play with Tensorflow!!! The assignment walks you through Tensorflow structure and basics in a very organized fashion.

Highly recommended!

By Ali n

Jul 7, 2020

Best course for learning Hyper parameter tuning, Regularization and Optimization topics further more the batch and other various optimization algos like momentum, Adam, Batch norm etc are much easier here. Please have a look on ground reality too, Take quiz before staring any course that this candidate is suitable or not

By Mihai L

Jan 21, 2018

This course is also interesting. The art of tuning hyper parameters and other optimization techniques are very interesting and nicely explained.

The introduction to Tensorflow and assignment is also interesting.Overall the difficulty is not high but the concepts are really powerful and important ,most scaffollding is done

By Vlad M

Sep 7, 2018

The course part is overall good.

The last assignment can be improved in two key ways:

The comment # Z3 = np.dot(W3,Z2) + b3 should be # Z3 = np.dot(W3,A2) + b3 - figured this out by myself without help from forums. :)

Also, the Adam optimization is not very apparent in the instructions - searched in the forums for issues.

By Evandro R d P J

Oct 22, 2020

Another wonderful course of this amazing specialization. I could say a lot of things, maybe even pages on how Professor Andrew it's the right person to teach you about Deep Learning but I'll shorten in this review and recommend the whole specialization for you! It's worthy and there's a lot of knowledge to be shared!

By Brad M

Aug 22, 2019

In my deep learning classes in academia, hyperparameter tuning was always "hand-waved" away - my questions were always deflected, or put off. This class answered every one of my questions, and made me more confident I'd be able to implement a DL system in industry, and be satisfied with the results. Very good course!

By Zeinab B

May 4, 2020

This course will cover everything you need regarding your neural network performance. I always had questions on why and when you use Adam, SGD, etc. and after this course, I have a much better understanding of how to choose hyperparameters and optimization methods. I highly recommend this course to ML practitioners.

By Toby K

Nov 1, 2019

I am working through the DL specialisation. Consistently good teaching style and the programming assignments are suitably pitched for getting the learner to pick up methods quickly e.g. Tensorflow syntax for self-application later. Good course and looking forward to the next in the series. Well done Andrew and team.

By Ankur T

Nov 21, 2018

word is not sufficient signup and experience it. For a deep learning beginner who already have math background can easily understand concept behind it but for implementation you need to refer extra materials on internet and book too. Andrew Ng explain only concept and recipe but for practice you will struggle hard.

By afshin m

Feb 5, 2018

This course is continuation and a requirement of the first course. Really like the learning style of how first course and the first 2 weeks of the second course taught neural networks by doing all the math and calculations manually and finally introduced Tensorflow with parallels of what was taught in the class.

By arulvenugopal

Dec 17, 2017

This is another excellent course in this specialization. I enjoyed the programming assignments. The instructions, tips made Tensor flow coding section to be easy . However, few blocks consumed more than few hours, due to placeholders. logic and the TF documentation is overwhelming. I am proceeding to next course.

By Wei L

Aug 26, 2017

This course is harder than the previous one. It teaches more details of tuning parameters and optimization in deep learning. In the end it also teaches tensorflow which is really helpful. It's like a programming course, nerally all the commands have been already provided, so it's not hard to get the code correct.